DetectChangePointRequest interface

Package:

@azure/ai-anomaly-detector

The request of change point detection.

Properties

customInterval	Custom Interval is used to set non-standard time interval, for example, if the series is 5 minutes, request can be set as {"granularity":"minutely", "customInterval":5}.
granularity	Can only be one of yearly, monthly, weekly, daily, hourly, minutely or secondly. Granularity is used for verify whether input series is valid.
period	Optional argument, periodic value of a time series. If the value is null or does not present, the API will determine the period automatically.
series	Time series data points. Points should be sorted by timestamp in ascending order to match the change point detection result.
stableTrendWindow	Optional argument, advanced model parameter, a default stableTrendWindow will be used in detection.
threshold	Optional argument, advanced model parameter, between 0.0-1.0, the lower the value is, the larger the trend error will be which means less change point will be accepted.

Property Details

customInterval

Custom Interval is used to set non-standard time interval, for example, if the series is 5 minutes, request can be set as {"granularity":"minutely", "customInterval":5}.

customInterval?: number

Property Value

number

granularity

Can only be one of yearly, monthly, weekly, daily, hourly, minutely or secondly. Granularity is used for verify whether input series is valid.

granularity: TimeGranularity

Property Value

TimeGranularity

period

Optional argument, periodic value of a time series. If the value is null or does not present, the API will determine the period automatically.

period?: number

Property Value

number

series

Time series data points. Points should be sorted by timestamp in ascending order to match the change point detection result.

series: TimeSeriesPoint[]

Property Value

TimeSeriesPoint[]

stableTrendWindow

Optional argument, advanced model parameter, a default stableTrendWindow will be used in detection.

stableTrendWindow?: number

Property Value

number

threshold

Optional argument, advanced model parameter, between 0.0-1.0, the lower the value is, the larger the trend error will be which means less change point will be accepted.

threshold?: number

Property Value

number